• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.357-360
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• 2005

In this paper we consider the well-known semiparametric proportional hazards (PH) models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enable us to estimate the survival curve when n < < p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA(cDNA) data.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.63-92
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• 2011

The purpose of this paper is to investigate a possibility of applying multimethodological approach for solving a dilemma. The motivation of this attempt is that the two different approaches, the system dynamics and the theory of constraints, resemble each other in having mental models for describing the target system and using graphic tools for representing those mental models. After a brief discussion on the comparison of the two approaches, a combined method applying to the problem of dilemma is suggested. For an experimental example, the proposed approach is applied to the sales and finance conflict on an inventory issue. The study shows that the suggested approach is able to complement each other's drawbacks. Especially constructing a stock-and-flow model and implementing a computer simulation would be very useful for quantifying the system's behavior which is hardly tracked down when applying the theory of constraints alone.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1402-1411
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• 2018

Nuclear-related facilities can be detrimentally affected by ground vibrations due to the collapse of adjacent cooling towers in nuclear power plants. To reduce this hazard risk, a design-oriented acceleration response spectrum (ARS) was proposed to predict the dynamic responses of nuclear-related facilities subjected to ground vibrations. For this purpose, 20 computational cases were performed based on cooling tower-soil numerical models developed in previous studies. This resulted in about 2664 ground vibration records to build a basic database and five complementary databases with consideration of primary factors that influence ground vibrations. Afterwards, these databases were applied to generate the design-oriented ARS using a response spectrum analysis approach. The proposed design-oriented ARS covers a wide range of natural periods up to 6 s and consists of an ascending portion, a plateau, and two connected descending portions. Spectral parameters were formulated based on statistical analysis. The spectrum was verified by comparing the representative acceleration magnitudes obtained from the design-oriented ARS with those from computational cases using cooling tower-soil numerical models with reasonable consistency.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.169-178
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• 2006

Traffic assignment has been used both for predicting travel demands and for evaluating the tools for alleviating congestion on road network in advance. Some assignment models have been proposed such as equivalent mathematical minimization method, variational inequality problem, nonlinear complementary problem and fixed point method, in following the principle of Wardrop (1952) that no driver can not Improve his travel cost by unilaterally changing his route. Recently Jin(2005a) presented a traffic assignment model based on dynamic process. This paper proposes a solution algorithm for the model of Jin and assesses the performances. Compared to the Frank-Wolfe method, which has been wildly used for solving the existing assignment models, the proposed algorithm is expected to be more efficient because it does not need to evaluate the objective function. Two numerical examples are used for assessing the algorithm, and they show that the algorithm converges to user equilibrium of Wardrop.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1837-1845
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• 2015

The longitudinal velocity is necessary for accurate vehicular positioning in urban environment. The pitch angle, which is a road slope, should be calculated to acquire the longitudinal velocity. However, it is impossible to consider very accurate pitch, when using a sensor and an algorithm. That's why process noise and positioning stimation error of IMU should be adjusted to the driving environment and fuse GPS, OBD data with ACF which consist of AKF, CF in this paper. Then, final pitch angle which is appropriate for driving environment is estimated by IMMKF in order to optimize the system model according to road slope models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.97-100
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• 2004

The identification of the DNA structure as a double-stranded helix consting of two nucleotide chain molecules was a milestone in modern molecular biology. The DNA chip technology is based on reverse hybridization that follows the principle of complementary binding of double-stranded DNA. DNA chip can be described as the deposition of defined nucleic acid sequences, probes, on a solid substrate to form a regular array of elements that are available for hybridization to complementary nucleic acids, targets. DNA chips based on cDNA clons, oligonucleotides and genomic clons have been developed for gene expression studies, genetic variation analysis and genomic changes associated with disease including cancers and genetic diseases. DNA chips for gene expression profiling can be used for functional analysis in human eel Is and animal models, disease-related gene studies, assessment of gene therapy, assessment of genetically modified food, and research for drug discovery. DNA chips for genetic variation detection can be used for the detection of mutations or chromosomal abnormalities in cnacers, drug resistances in cancer cells or pathogenic microbes, histocompatibility analysis for transplantation, individual identification for forensic medicine, and detection and discrimination of pathogenic microbes. The DNA chip will be generalized as a useful tool in clinical diagnostics in near future. Lab-on-a chip and informatics will facilitate the development of a variety of DNA chips for diagnostic purpose.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.305-326
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• 2019

Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets. However, amount of recent researches are vulnerable to heavy occlusions, irregular deformations and so on. In this paper, we intend to solve these problems and handle the contradiction between accuracy and real-time in the framework of tracking-by-detection. Firstly, we propose an innovative strategy to combine the template and color-based models instead of a simple linear superposition and rely on the strengths of both to promote the accuracy. Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding to features in the background. Thirdly, we utilize a discriminative multi-scale estimate method to solve the problem of scale variations. Finally, we research strategies to limit the computational complexity of our tracker. Abundant experiments demonstrate that our tracker performs superiorly against several advanced algorithms on both the OTB2013 and OTB2015 datasets while maintaining the high frame rates.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.380-380
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• 2019

본 연구에서는 일반 상호보완이론(Generalized Complementary Relationship, GCR)을 활용하여 실제증발산량을 추정하고, 추정한 실제증발산량기반 가뭄지수로부터 미국 전역에 대한 가뭄을 해석하는 것이다. 월강수량, 최고 최저기온, 이슬점온도 등의 필요한 기상자료는 Parameter-elevation Relationships on Independent Slopes Model(PRISM)으로부터 수집하였으며, 1981년부터 2015년까지 총 35년의 미국 전역에 대한 실제증발산량을 추정하였다. 대상지역의 유역평균 강수량과 유출량의 차(P-Q)와 North American Land Data Assimilation System(NLDAS-2) Noah 지표모형(Land surface models)으로 산정한 실제증발산량과 비교 검증하였다. GCR로부터 증발산 부족량(ET Deficit, ETD)을 산정하고 이를 표준정규화하여 미국 전역에 대해 Standardized Evapotranspiration Deficit Index(SEDI)를 산정하였다. 본 연구로부터 GCR 기반 실제증발산량은 P-Q의 값과 상관계수가 0.94로 매우 높은 상관성을 보였으며, NLDAS-2 Noah모형의 실제증발산량보다 다소 크게 추정하는 경향을 보였다. SEDI와 Standard Precipitation Index(SPI)의 상관성은 지속시간이 클수록 더 크게 나타났다. 증발산 상호보완이론활용 실제증발산기반 SEDI이 강수자료를 사용하지 않고서도 적절한 가뭄해석에 이용될 수 있을 것으로 판단된다.

• Journal of The Korean Astronomical Society
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• v.53 no.6
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• pp.139-147
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• 2020

The sunspot area is a critical physical quantity for assessing the solar activity level; forecasts of the sunspot area are of great importance for studies of the solar activity and space weather. We developed an innovative hybrid model prediction method by integrating the complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM). The time series is first decomposed into intrinsic mode functions (IMFs) with different frequencies by CEEMD; these IMFs can be divided into three groups, a high-frequency group, a low-frequency group, and a trend group. The ELM forecasting models are established to forecast the three groups separately. The final forecast results are obtained by summing up the forecast values of each group. The proposed hybrid model is applied to the smoothed monthly mean sunspot area archived at NASA's Marshall Space Flight Center (MSFC). We find a mean absolute percentage error (MAPE) and a root mean square error (RMSE) of 1.80% and 9.75, respectively, which indicates that: (1) for the CEEMD-ELM model, the predicted sunspot area is in good agreement with the observed one; (2) the proposed model outperforms previous approaches in terms of prediction accuracy and operational efficiency.

• Journal of KIBIM
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• v.9 no.2
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• pp.29-44
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• 2019

This paper is to explore examples of complementary use of digital and physical models. The reason for this is to suggest a method for commercializing architectural design considering high technology. These cases are the practical and educational environment in which design processes based on digital computation technology are performed. Also, in this environment, analog design media (eg, physical models) still being used in the design process using digital computing. Indeed, in this environment, designers are exploiting digital and physical models to address the types of risks that can be discovered when designs are implemented and these risks. By analyzing these cases, we define the roles of digital and physical models to visualize and resolve risks. This paper focuses on one of method as "prototyping", which is used in the field of machinery and is a difficult method to carry out in the conventional design process. In particular, designers look for benefits that encourage designers in utilizing current digital computation technologies (eg, parametric design, simulation, building information models, and digital fabrication). Among the roles of the physical model, roles that can not be replaced by the digital model are explored. It is clear that this case-based study has difficulty in generalizing the design method. However, it helps the designers of today's practical and educational environment to verify and design the actual details of construction and operation when applying and developing unfamiliar materials and methods in the field of architecture.